While artificial intelligence (AI) has been around for decades, the world is starting to take note of its powerful capabilities, especially with the launch of ChatGPT. From what your see on your social media feeds to using a ride share app, AI has been hard at work behind the scenes.
AI has pushed business leaders across industries to understand how this technology works and how they can use it to do away with time-consuming processes, improve performance outcomes, and drive enterprise agility. According to the State of AI Report, 94% of business leaders believe AI will be critical to their organization’s success over the next five years.
However, understanding the value of AI is one thing, and successfully deploying AI technologies is another.
Why Companies Aren't Ready for AI
What’s holding organizations back from incorporating AI? Simply put, data–it’s the driving force behind powerful AI technologies.
Most organizations cannot produce the data they need to implement AI successfully because they’re clinging to manual reporting and processes. As a result, critical decisions are delayed, blocked, or they completely miss the mark, and business agility is stalled.
So, how can your organization adopt AI in a way that feels right for your business? In this article, we explore how you can leverage the value of AI by investing in technologies that deliver the real-time, data-driven business intelligence needed to drive value at scale.
In Our Data Era
To establish benchmarks, set goals, and make strategic decisions, businesses need quality data. And that data must be accurate, comparable, and consistent over time.
However, most organizations face the challenge of having their data dispersed across enterprise silos, which prevents them from making well-informed decisions. On top of all this, their teams are stuck in their old ways of inputting data into disparate legacy systems like spreadsheets.
Just take this global retailer, for example. The Fortune 40 company struggled to achieve enterprise agility because teams would begin work in Excel, move data into Jira, and then export everything back into Excel for reporting purposes. Not only were they wasting time, but this reporting process proved ineffective since it didn’t produce the enterprise intelligence the retailer needed to make smart decisions fast.
Operating with disconnected processes and tools means that it takes longer to acquire data, but even then, that data is inconsistent, or worse–inaccurate. Peter Drucker said it best, “If you can’t measure it, you can’t manage it.”
Preparing Your Data for AI
For AI to produce the insights your organization needs, it has to be able to find your data and understand it. If multiple users are manually updating spreadsheets, then your data is destined to be inconsistent.
You’ve probably witnessed this common scenario before: last month, revenue was in column A; this month revenue is in column B. Last month, report A was in file folder B; this month report A is in file folder C. Organizations can’t leverage AI capabilities if data structures are constantly changing and AI doesn’t know what to look for or where to find it.
Data should also flow automatically into a data repository, whether that is a data lake, database, or a configured BI tool. Thankfully, most modern databases are on platforms that speak to one another via connectors and APIs. This allows data to be extracted and shared within and across the organization.
Connecting Strategy to Data
So, how can your organization adapt to an AI-disrupted market if your strategy lives in a Word document? How do you quickly move capacity and resources if you are sorting through spreadsheets to make strategic decisions? The answer is: you can’t because your spreadsheets are slowing you down and producing weak data.
Traditional project management systems are blocking organizations from building an agile enterprise because they don’t produce the data needed to generate actionable insights. And this lack of quality data is costing organizations big time. According to a study from McKinsey, the average Fortune 500 company wastes $250 million per year due to poor decision-making.
To be part of today’s fast-moving wave of AI, your business strategy has to be data-driven. This means you need to invest in technology that enables you to tie your data back to the work your teams are doing and understand how that work tracks against your strategic initiatives.
Enterprise agility tools like Jira Align help accelerate this process by aggregating work being done across all levels of the organization and delivering real-time business intelligence that stakeholders need to make data-driven decisions. Jira Align allows you to connect your strategy data to your delivery data, so anyone, at any time, can understand the importance of any given piece of work.
How to Become an AI-Driven Enterprise
AI is more than just a trend–it’s here to stay. And it’s moving fast.
Don’t let your company get left behind the AI wave because you are clinging to your legacy systems and old ways of working. To leverage the value of AI, you must first recognize the value of your data.
Here at Praecipio, we can help you build a connected, AI-ready enterprise. Our ebook It's Not You, It's Your Data: How Good Data Taxonomy Will Improve Your AI Outputs walks you through how to improve your data infrastructure with the right technology and provides you with key action items for achieving a successful AI deployment.
When you download this resource, you will also learn our secret sauce for integrating tools with AI to deliver the data-driven business insights needed for your organization to achieve enterprise agility.
If you want to know more about adopting AI and the technology that facilitates this process, contact us and we will show you how to harness AI’s powerful capabilities.
